A Self-Consistent Method to Assess Air Quality Co-Benefits from US Climate Policies

Air quality co-benefits can potentially reduce the costs of greenhouse gas mitigation. However, while many studies of the cost of greenhouse gas mitigation model the full macroeconomic welfare impacts, most studies of air quality co-benefits do not. We employ a US computable general equilibrium economic model previously linked to an air quality modeling system, and enhance it to represent the economy-wide welfare impacts of fine particulate matter. We present a first application of this method to explore the efficiency and the distributional implications of a clean energy standard (CES) and a cap–and–trade (CAT) program that both reduce CO2 emission by 10% in 2030 relative to 2006. We find that co-benefits from fine particulate matter reduction completely offset policy costs by 110% (40% to 190%), transforming the net welfare impact of the CAT into a gain of $1 (-$5 to $7) billion 2005 US$. For the CES, the corresponding co-benefit (median $8; $3 to $14)/tCO2 is a smaller fraction (median 5%; 2% to 9%) of its higher policy cost. The eastern US garners 78% and 71% of co-benefits for the CES and CAT, respectively. By representing the effects of pollution-related morbidities and mortalities as an impact to labor and the demand for health services, we find that the welfare impact per unit of reduced pollution varies by region. These interregional differences can enhance the preference of some regions, like Texas, for a CAT over a CES, or switch the calculation of which policy yields higher co-benefits, compared to an approach that uses one valuation for all regions. This framework could be applied to quantify consistent air quality impacts of other pricing instruments, subnational trading programs, or green tax swaps.The authors gratefully acknowledge the financial support for this work provided by the MIT Joint Program on the Science and Policy of Global Change through a consortium of industrial sponsors and Federal grants. Additionally, the authors acknowledge support from: the US EPA under the Science to Achieve Results (STAR) program (#R834279); MIT's Leading Technology and Policy Initiative; US Department of Energy Office of Science grant DE-FG02-94ER61937; the MIT Energy Initiative Total Energy Fellowship (Saari); and a MIT Martin Family Society Fellowship (Saari)